Search:
Computing and Library Services - delivering an inspiring information environment

INVESTIGATION OF DYNAMIC RESPONSES OF ON-ROTOR WIRELESS SENSORS FOR CONDITION MONITORING OF ROTATING MACHINES

Mones, Zainab (2018) INVESTIGATION OF DYNAMIC RESPONSES OF ON-ROTOR WIRELESS SENSORS FOR CONDITION MONITORING OF ROTATING MACHINES. Doctoral thesis, University of Huddersfield.

[img]
Preview
PDF - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (4MB) | Preview

Abstract

The most common sensors that are used to monitor the condition of a machine health are wired accelerometers. The big advantages of using these types of accelerometers are their high performance and good stability. However, they have certain drawbacks as well. These accelerometers are large in size and require a cable for external power source. Hence a more reliable and cheaper alternatives of these conventional accelerometers are needed that can eliminate the drawbacks of the wired accelerometers. This thesis reports the application of wireless Micro-Electro-Mechanical System (MEMS) accelerometer for machinery condition monitoring. These sensors are so small that they can be easily mounted on the rotating machine parts and can acquire dynamic information very accurately.

One critical problem in using an on-rotor accelerometer is to extract the true tangential acceleration from the MEMS outputs. In this research, the mathematical model of an on-rotor triaxial MEMS accelerometer output signals is studied, and methods to eliminate the gravitational effect projected on X-axis (tangential direction) are proposed. The true tangential acceleration that correlates to the instantaneous angular speed (IAS) is reconstructed by combining two orthogonal outputs from the sensor that also contain gravitational accelerations.

To provide more accurate dynamic characteristics of the rotating machine and hence achieving high-performance monitoring, a tiny MEMS accelerometer (AX3 data logger) has been used to obtain the on-rotor acceleration data for monitoring a two-stage reciprocating compressor (RC) based on the reconstruction of instantaneous angular speed (IAS). The findings from the experiments show that the conditions of the RC can be monitored and different faults can be identified using only one on-rotor MEMS accelerometer installed on compressor’ flywheel.

In addition, the data collection method is improved by considering the wireless data transmission technique which enables online condition monitoring of the compressor. Thus, a wireless MEMS accelerometer node is mounted on the RC to measure the on-rotor acceleration signals. The node allows the measured acceleration data to be streamed to a remote host computer via Bluetooth Low Energy (BLE) module. In addition, the device is miniaturised so that can be conveniently mounted on a rotating rotor and can be driven by a battery powered microcontroller. To benchmark the wireless sensor performance, an incremental optical encoder was installed on the compressor flywheel to acquire the instantaneous angular speed (IAS) signal.

Furthermore, conventional accelerometer mounted on the machine’s housing provide lower accuracy in diagnosis the faults for planetary gearboxes because of the planet gears’ varying mesh excitation due to its carrier movement. In contrast, installation of the smaller AX3 MEMS accelerometers is done at diametrically opposite direction to the each other of the planetary gearbox’s low-speed input shaft, allowing measurement of the acceleration signals which are used for condition monitoring of the gearbox. The findings from the experiments demonstrate that when tangential acceleration is measured at the planetary gearbox’s low-speed input shaft, effective fault identification is possible, offering reliability and economy in monitoring the health of planetary gearboxes.

Item Type: Thesis (Doctoral)
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TJ Mechanical engineering and machinery
Schools: School of Computing and Engineering
Depositing User: Rebecca Hill
Date Deposited: 02 Apr 2019 13:10
Last Modified: 02 Apr 2019 13:15
URI: http://eprints.hud.ac.uk/id/eprint/34837

Downloads

Downloads per month over past year

Repository Staff Only: item control page

View Item View Item

University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©